Demographic Insights into the Adoption of Digital Innovations in Agriculture: Segmenting Adopters and Non-Adopters among Vietnamese Farmers

As digital technology adoption expands, it offers significant potential to advance sustainable agricultural practices. This study investigates the segmentation between adopters and non- adopters of digital agricultural technology in Vietnam, drawing on data from 568 farmers. Chi-square tests reveal potential significant associations between adoption status and demographic factors, including age, farm size, revenue, and education levels. These findings outline the key demographic characteristics influencing adoption behavior. To further explore adoption intention, one-way ANOVA and Welch’s tests compare intent across different age, experience, and regional groups. While age shows no significant effect, prior experience with agricultural technology is strongly associated with adoption intent, indicating the importance of familiarity with technology. Regional analysis highlights notable variations, with differences observed in adoption intent among farmers in the Central, Northern, and Southern regions. These findings provide valuable insights into the demographic and regional factors influencing digital technology adoption in agriculture. By identifying distinct adoption patterns and understanding potential barriers, the study offers practical guidance for policymakers and stakeholders. Targeted, region-specific strategies can be developed to address unique challenges, encourage broader adoption, and support the transition to high-tech, sustainable farming practices across Vietnam.

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Publication Details

Journal
Journal of Development and Integration
Published
2025-09-15
DOI
https://doi.org/10.61602/jdi.2025.83.07
Primary Topic
COVID-19 Pandemic Impacts
Type
article
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article

Demographic Insights into the Adoption of Digital Innovations in Agriculture: Segmenting Adopters and Non-Adopters among Vietnamese Farmers

Nguyễn Thanh Lâm, Nam Hoang Tran
Journal of Development and Integration
COVID-19 Pandemic Impacts
article

Demographic Insights into the Adoption of Digital Innovations in Agriculture: Segmenting Adopters and Non-Adopters among Vietnamese Farmers

Nguyễn Thanh Lâm, Nam Hoang Tran
article en

Abstract

As digital technology adoption expands, it offers significant potential to advance sustainable agricultural practices. This study investigates the segmentation between adopters and non- adopters of digital agricultural technology in Vietnam, drawing on data from 568 farmers. Chi-square tests reveal potential significant associations between adoption status and demographic factors, including age, farm size, revenue, and education levels. These findings outline the key demographic characteristics influencing adoption behavior. To further explore adoption intention, one-way ANOVA and Welch’s tests compare intent across different age, experience, and regional groups. While age shows no significant effect, prior experience with agricultural technology is strongly associated with adoption intent, indicating the importance of familiarity with technology. Regional analysis highlights notable variations, with differences observed in adoption intent among farmers in the Central, Northern, and Southern regions. These findings provide valuable insights into the demographic and regional factors influencing digital technology adoption in agriculture. By identifying distinct adoption patterns and understanding potential barriers, the study offers practical guidance for policymakers and stakeholders. Targeted, region-specific strategies can be developed to address unique challenges, encourage broader adoption, and support the transition to high-tech, sustainable farming practices across Vietnam.

Journal of Development and Integration(83)
Openalex Percentile: Top 66%
COVID-19 Pandemic Impacts
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Demographic Insights into the Adoption of Digital Innovations in Agriculture: Segmenting Adopters and Non-Adopters among Vietnamese Farmers — Nguyễn Thanh Lâm, Nam Hoang Tran · Journal of Development and Integration (2025) | TGRS Research Map | TGRS